Artificial Intelligence for Nonprofits and other Social Good Organizations

In the movies, the emergence of Artificial Intelligence usually leads to robotic cyborgs going haywire, machines that threaten humanity, or a choice between a red or blue pill. The plotline almost always assumes the worst will happen. Thankfully, these aren’t the droids you’re looking for. Instead, AI has tremendous potential to help improve performance for nonprofits and social good organizations and drive meaningful change in the world.

But first we need to separate the buzz words and bravado from the real transformation that is taking place with AI for nonprofits:.

What is Artificial Intelligence and Why Should You Care?

Artificial Intelligence is, at its heart, enabling machines to process information and learn. AI is a broad set of disciplines and technologies that perform tasks and solve problems once only possible by humans. The ability for technology to learn without every single step of a process having to be programmed is a tremendous breakthrough.

A line of code is static and it just does the same routine over and over again. But artificial intelligence has the ability to constantly learn and improve over time. It does not get exhausted from running millions of scenarios or interrupted by meetings. And unlike that piece of code that waits for the user to do something, artificial intelligence proactively uses a number of strategies to take action deliberately.

This presents tremendous opportunities for nonprofits and other social good organizations, like universities, foundations, hospitals, and other cause-minded institutions. While some industries are concerned about how big data and AI could lead to a reduction in jobs, that is not the case among nonprofits. We know that social good organizations are constantly strapped for resources that allow them to meet their missions. Using data, analytics, and AI can allow nonprofits to extend their capacity and capabilities. AI won’t take jobs in the nonprofit sector— it will make them more valuable.

The Past and Present of Artificial Intelligence

The pursuit of meaningful artificial intelligence has been a work in progress for over 60 years now. A summer research project at Dartmouth College in the 1950s was pivotal in defining the field and casting a vision for the technologies that are today transforming our world.

An attempt will be made to find how to make machines use language, form abstractions, and concepts, solve kinds of problems now reserved for humans, and improve themselves. – Dartmouth Summer Research Project Proposal on Artificial Intelligence, 1955.

Fast forward several decades from those modest brainstorming sessions, and AI has moved from the theoretical to the actual. The signs of applied artificial intelligence, predictive analytics, machine learning, and learning systems are all around us now. Remember Microsoft’s Clippy, the awkward paper clip that suddenly appeared in your software? That was an early attempt to use algorithms to understand user behavior and prescribe recommendations.

While it may not have been perfect, Clippy should be considered the grandfather of Apple’s Siri, Google’s Assistant, Microsoft’s Cortana, and Amazon’s Alexa. These tools and technologies have had years to mature and become more intelligent in ways that add value to our everyday lives. This maturation is what allows Netflix and Spotify to make better recommendations. This is what Google’s Waze uses to find you a better route home. This is how Blackbaud helps nonprofits make better decisions around supporter engagement.

How Data Fuels the Growth of Artificial Intelligence

But, as powerful as artificial intelligence has grown, it is important to remember that AI is just one piece of the problem-solving puzzle. The potential of artificial intelligence for nonprofits is deeply interwoven with the potential of data— because data is the material that AI is learning from.

In the social good community, data is the most abundant element. Data informs us about supporters, members, and stakeholders. Data provides insights into the success of our engagements, campaigns, and programs. Data makes it possible to understand the impact of our actions and the reach of our outcomes.

If you’re dreaming big about the potential of AI for nonprofits, know that the first questions you need to be asking are about data, and how good it is. Are your AI capabilities being “fed” with data that is meaningful to your cause and the outcomes you’re pursuing?

Artificial Intelligence for Nonprofits Can Drive Real Impact

The real formula for success in the social good community is the combination of the right data, insightful analytics and reporting, applied artificial intelligence, and the right expertise. That last part of the equation can easily be overlooked. The successful use of data, analytics, and AI for nonprofits still requires one very important element—humans. And in the nonprofit sector, it requires the skill and expertise of social good scientists. What I mean by this is, in the social good community, we require solutions that have been specifically designed for the unique needs of our sector.

All the artificial intelligence capabilities in the world won’t make tools designed for fundamentally different purposes useful for the unique needs of this sector. What we do as nonprofit and social good organizations is indeed different than the retail or petrochemical or pharmaceutical world. We are not trying to get people to buy more soda-pop— we need them to help us change the world.

This is a different approach than a lot of the hype we hear about using big data and AI. Success requires the right data, contextual expertise, and continual learning. But when these things come together, the capabilities can drive real impact. For example, Blackbaud has been using AI and machine learning to surface recommendations to fundraisers directly in their software applications. Nonprofit professionals don’t need special tools or skills to take action on the information. It’s just a capability they have access to all the time.